Abstract Background Semantic annotators and Natural Language Processing (NLP)
methods for Named Entity Recognition and Linking (NER+ L) require plenty of training and …

New approaches to biomedical text mining crucially depend on the existence of
comprehensive annotated corpora. Such corpora, commonly called gold standards, are …

Motivation Annotation tools are applied to build training and test corpora, which are
essential for the development and evaluation of new natural language processing …

The annotation of entities with concepts from standardized terminologies and ontologies is
of high importance in the life sciences to enhance semantic interoperability, information …

Biomedical documents such as Electronic Health Records (EHRs) contain a large amount of
information in an unstructured format. The data in EHRs is a hugely valuable resource …

Biomedical texts are a rich information source that cannot be ignored. There are several text
annotation tools that may be used to extract useful information from these texts. However …

Background and objectives Document annotation is a key task in the development of Text
Mining methods and applications. High quality annotated corpora are invaluable, but their …

Automatic annotation of text is an important complement to manual annotation, because the
latter is highly labour intensive. We have developed a fast dictionary-based named entity …

Named entity recognition (NER) is an important step in biomedical information extraction
pipelines. Tools for NER should be easy to use, cover multiple entity types, be highly …

Ever-expanding volumes of biomedical text require automated semantic annotation
techniques to curate and put to best use. An established field of research seeks to link …